Abstract

Readers will gain a basic understanding of the tribological behavior of polymer-based composites after reading this chapter. The chapter proceeds with an overview of the several types of fillers that are utilized in polymers. The properties of polymer-based nanocomposites that define their performance have been explained. To understand how the two mating surfaces are interacting with each other, three levels of interaction between the mating surfaces have been discussed. Cohesive and interfacial wear mechanisms have been explained in a lucid manner. The chapter progresses with a detailed discussion on wear theories, viz., adhesive wear, abrasion wear, delamination wear, fatigue wear, transfer wear, chemical wear, fretting wear, and erosion. Various models have been put forward for estimating the wear volume. The Archard adhesion model, the Rabinowicz abrasion model, the Ratner-Lancaster abrasion model, the Bitter model for erosion, and the Finnie model for erosion are a few of them. Analyzing the wear process and sliding friction of polymer composites requires high cost and is also time-consuming. To make this task simple, the use of a predictive design tool called artificial neural network (ANN) has been shown with the help of a case study. Finally, the use of molecular dynamics (MD) simulation for evaluating the wear properties of polymer-based composites has been explained with the help of an illustrative example. The researcher should be able to apply the ANN and MD methods to analyze the wear behavior of graphene-reinforced polymer composites after completing this module.

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